Senior Machine Learning Engineer (Medical Imaging)
Job description
About Entrada AI
Entrada AI is a specialized consulting partner and a strategic portfolio company of Databricks Ventures. We were recently named the Genie Partner of the Year (2026) for our work deploying Databricks Genie at enterprise scale—bridging the gap between AI ambition and the trusted, governed data required for accurate responses. With over 150 Databricks projects delivered, we unlock self-service analytics for Fortune 500 leaders.
Databricks invested in us because of our technical excellence, placing us in the "inner circle" of the ecosystem. For our engineers, this means direct access to product roadmaps, private previews, and the teams building the platform. You will join a team of industry veterans who value clean architecture over quick fixes. We don't just maintain pipelines; we solve complex architectural challenges.
About the Role
As a Senior Machine Learning Engineer (Medical Imaging), you will lead the design and deployment of end-to-end AI lifecycles for global healthcare and life sciences clients. You will move beyond building isolated models to architecting scalable, production-grade ML systems on the Databricks Lakehouse. This role requires a unique intersection of deep learning expertise, data engineering rigour, and a consultant’s mindset — balancing technical sophistication with the ability to advise stakeholders on clinical validation, regulatory compliance, and long-term AI strategy.
Key Responsibilities
AI Architecture & Development: Design and implement scalable computer vision pipelines using PyTorch or TensorFlow, leveraging Databricks Runtime for ML to process large-scale medical imaging datasets (DICOM, NIfTI).
Production MLOps: Architect end-to-end MLOps workflows using MLflow for experiment tracking, model versioning, and seamless transition from research to production-grade Model Serving.
Imaging Optimization: Develop efficient data loaders and preprocessing steps for high-dimensional medical data, utilizing Apache Spark to parallelize image transformation and feature extraction.
Governance & Compliance: Enforce rigorous data lineage and security protocols via Unity Catalog, ensuring all model training and inference processes meet healthcare regulatory standards (HIPAA/GDPR/HITRUST).
Technical Leadership: Act as a strategic advisor for clients, guiding them on the "build vs. buy" of medical AI tools and sharing best practices on model interpretability and bias mitigation in clinical settings.
Standardization: Implement CI/CD for ML (Git integration, Databricks Asset Bundles) and promote the use of Feature Stores to ensure consistency between training and real-time inference.
Requirements
Experience: 5+ years in Machine Learning or Data Science, with at least 3 years of deep, hands-on experience deploying models within the Databricks ecosystem.
Medical Imaging Domain: Proven experience handling medical imaging formats (DICOM, NIfTI, WSI) and familiarity with specialized libraries such as MONAI, SimpleITK, or OpenCV.
Core Engineering: Advanced proficiency in Python (specifically the PyData stack) and SQL. Experience with PySpark for large-scale data manipulation is essential.
Cloud & Infrastructure: Production experience in Azure (Azure Machine Learning, ADLS Gen2) or AWS (SageMaker, S3), with a focus on GPU instance management and cost optimization.
Modern ML Stack: Expertise in MLflow for the full lifecycle and experience with Delta Lake to manage unstructured imaging metadata. Familiarity with Databricks Model Serving or TorchServe.
Modeling Depth: Strong understanding of Deep Learning architectures (CNNs, Transformers, SegNet) and evaluation metrics specific to medical diagnostics
Communication: Fluent English (C1+) for direct client collaboration; ability to translate complex algorithmic concepts into strategic business value for non-technical stakeholders.
Credentials: A commitment to technical excellence, ideally backed by certifications such as Databricks Machine Learning Professional or specialized Cloud AI certifications.
The Offer
Cooperation Models:
Poland: Available via Employment Contract (UoP) or B2B.
Romania/ Greece: Available via B2B only.
100% Remote: Full flexibility to work from anywhere in Poland/ Romania / Greece
High-End Tech: Apple MacBook Air M4 15" provided to all engineers.
Referral Bonus: Bonus for bringing other top-tier engineers to the team.
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Professional Growth:
Certification Support: Coverage for all Databricks technical certifications.
Industry Leadership: Support in reaching the highest tiers of Databricks expertise (such as the Champion program) tailored to your specific career track.
Personal Branding: Opportunities to present at global industry conferences and contribute to technical thought leadership.
Expert Mentorship: Direct collaboration with Databricks MVPs and core product teams, giving you a front-row seat to the platform's evolution.
Recruitment Process
Introductory Call (20 min): Short conversation with our Recruiter to discuss your background and expectations.
Technical Interview (60 min): Deep dive into your technical skills with our engineering team.
Optional Client Interview: Required only in specific cases.
Decision & Offer: We aim to close the process and provide feedback efficiently.
Originally posted on Himalayas